kislayabhi / gpu_badmm_mt_rpca Goto Github PK

To compile and run RPCA: ./compile_and_run.sh

Mass transportation problem: C, a, b. The default a = 1, b = 1;

1. The file C,a,b for mass transportation problem are generated using matlab storing in a binary file in row-major order. For example, m = 1024; n = m; C = rand(m,n); fid = fopen([int2str(n) 'C.dat'],'w'); fwrite(fid,[m,n],'int'); fwrite(fid,C','float'); fclose(fid);

2. compile cuda code and tune parameters nvcc -o badmm_mt badmm_mt.cu badmm_kernel.cu -lcublas -arch sm_13 nvprof ./badmm_mt dim_file_name rho max_iteration tolerance_stop_badmm num_steps_print save_output a. dim_file_name: the name of cost matrix is stored in binary with name dim1024C.dat. The name of a,b files are dim1024a.dat and dim*1024b.dat b. rho (float): the parameter of badmm c. max_iteration (int): the maximum number of iterations of badmm d. tol (float): the stopping condition of primal and dual residuals of badmm. If less than tol, badmm will stop. e. num_steps_print (int): print intermediate results every num_steps_print step. If num_steps_print = 0, no print. f. save_output: write the final result of mass transportation into a binary file named X_out.dat The default values will be chosen if setting them to zero or no specification

3. read X_out to matlab fid = fopen('X_out.dat','r'); X = fread(fid,[n,m],'float'); fclose(fid); X = X';